






"""simple docstring"""
import json
import os
import unittest
from typing import Tuple

from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from transformers.testing_utils import require_phonemizer

from ...test_tokenization_common import TokenizerTesterMixin



@require_phonemizer
class        UpperCamelCase__ (				a_							,	unittest.TestCase):







    """simple docstring"""
    __UpperCAmelCase           = WavaVecaPhonemeCTCTokenizer
    __UpperCAmelCase           = False







    def 				a__			(		self :	int ):





           '''simple docstring'''

           super().setUp()

           __magic_name__      				=    (
               '<s> <pad> </s> <unk> n s t ə l a i k d m ɛ ɾ e ɪ p o ɐ z ð f j v b ɹ ʁ ʊ iː r w ʌ u ɡ æ aɪ ʃ h ɔ ɑː '
               'ŋ ɚ eɪ β uː y ɑ̃ oʊ ᵻ eː θ aʊ ts oː ɔ̃ ɣ ɜ ɑ dʒ əl x ɜː ç ʒ tʃ ɔː ɑːɹ ɛ̃ ʎ ɔːɹ ʋ aː ɕ œ ø oːɹ ɲ yː '
               'ʔ iə i5 s. tɕ ?? nʲ ɛː œ̃ ɭ ɔø ʑ tʲ ɨ ɛɹ ts. rʲ ɪɹ ɭʲ i.5 ɔɪ q sʲ u5 ʊɹ iɜ a5 iɛ5 øː ʕ ja əɜ th ɑ5 '
               'oɪ dʲ ə5 tɕh ts.h mʲ ɯ dʑ vʲ e̞ tʃʲ ei5 o5 onɡ5 ɑu5 iɑ5 ai5 aɪɚ kh ə1 ʐ i2 ʉ ħ t[ aɪə ʲ ju ə2 u2 oɜ '
               'pː iɛɜ ou5 y5 uɜ tː uo5 d[ uoɜ tsh ɑɜ ɵ i̪5 uei5 ɟ aɜ ɑɨ i.ɜ eʊ o2 ɐ̃ ä pʲ kʲ n̩ ɒ ph ɑu2 uɨ əɪ ɫ ɬ '
               'yɜ bʲ ɑ2 s̪ aiɜ χ ɐ̃ʊ̃ 1 ə4 yæɜ a2 ɨː t̪ iouɜ ũ onɡɜ aɨ iɛ2 ɔɨ ɑuɜ o̞ ei2 iou2 c kː y2 ɖ oe dˤ yɛɜ '
               'əʊ S ɡʲ onɡ2 u" eiɜ ʈ ɯᵝ iou5 dZ r̝̊ i.2 tS s^ ʝ yə5 iɑɜ uə5 pf ɨu iɑ2 ou2 ər2 fʲ ai2 r̝ uəɜ ɳ əɨ '
               'ua5 uɪ ɽ bː yu5 uo2 yɛ5 l̩ ɻ ərɜ ʂ i̪2 ouɜ uaɜ a. a.ː yæ5 dː r̩ ee ɪu ər5 i̪ ɜ æi u: i.ː t^ o1 ɪ^ '
               'ai ueiɜ æː ɛɪ eə i. ɴ ie ua2 ɑ1 o4 tʃː o: ɑ: u1 N i̪1 au yæ2 u. qː yəɜ y: kʰ tʃʰ iʊ sx õ uo tʰ '
               'uai5 bʰ u.ː uə2 ʊə d^ s̪ː yiɜ dʰ r. oe: i1 ɟː yu2 nʲʲ i̪4 uei2 tsʲ ɸ ĩ ɑ4 t̪ː eɑ u4 e: tsː ʈʰ ɡʰ '
               'ɯɯ dʒʲ ʂʲ X ɵː uaiɜ tɕʲ ã t^ː ẽː yɛ2 cː i.1 ɛʊ dˤdˤ dʒː i4 ɡː yi ɕʲ ɟʰ pʰ dʑʲ yuɜ ua1 ua4 æiː ɐɐ '
               'ui iou1 ʊː a1 iou4 cʰ iɛ1 yə2 ɖʰ ẽ ʒʲ ää ər4 iːː ɪː iɑ1 ər1 œː øi ɪuː cʰcʰ əː1 iː1 ũ kʰː o̞o̞ xʲ '
               'ou1 iɛ4 e̞e̞ y1 dzː dʲʲ dʰː ɯᵝɯᵝ lː uo1 i.4 i: yɛ5ʲ a4'
           ).split(' ' )
           __magic_name__      				=    dict(zip(UpperCamelCase_				,    range(len(UpperCamelCase_ ) ) ) )

           __magic_name__      				=    {'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}

           __magic_name__      				=    os.path.join(self.tmpdirname				,    VOCAB_FILES_NAMES['vocab_file'] )
           with open(self.vocab_file				,    'w'				,    encoding='utf-8' ) as fp:
                  fp.write(json.dumps(UpperCamelCase_ ) + '\n' )







    def 				a__			(		self :	List[Any]				,    UpperCamelCase_ :	Any				,    UpperCamelCase_ :	str=False				,    UpperCamelCase_ :	str=2_0				,    UpperCamelCase_ :	Optional[int]=5 ):





           '''simple docstring'''

           __magic_name__      				=    [(i, tokenizer.decode([i]				,    clean_up_tokenization_spaces=UpperCamelCase_ )) for i in range(len(UpperCamelCase_ ) )]
           __magic_name__      				=    list(filter(lambda UpperCamelCase_ : [t[0]] == tokenizer.encode(t[1]				,    do_phonemize=UpperCamelCase_ )				,    UpperCamelCase_ ) )
           if max_length is not None and len(UpperCamelCase_ ) > max_length:
                  __magic_name__      				=    toks[:max_length]
           if min_length is not None and len(UpperCamelCase_ ) < min_length and len(UpperCamelCase_ ) > 0:
                  while len(UpperCamelCase_ ) < min_length:
                         __magic_name__      				=    toks + toks
        # toks_str = [t[1] for t in toks]
           __magic_name__      				=    [t[0] for t in toks]

           # Ensure consistency
           __magic_name__      				=    tokenizer.decode(UpperCamelCase_				,    clean_up_tokenization_spaces=UpperCamelCase_ )
           if " " not in output_txt and len(UpperCamelCase_ ) > 1:
                  __magic_name__      				=    (
                      tokenizer.decode([toks_ids[0]]				,    clean_up_tokenization_spaces=UpperCamelCase_ )
                      + ' '
                      + tokenizer.decode(toks_ids[1:]				,    clean_up_tokenization_spaces=UpperCamelCase_ )
                  )
           if with_prefix_space:
                  __magic_name__      				=    ' ' + output_txt
           __magic_name__      				=    tokenizer.encode(UpperCamelCase_				,    add_special_tokens=UpperCamelCase_ )
           return output_txt, output_ids







    def 				a__			(		self :	List[str]				,    **UpperCamelCase_ :	Tuple ):





           '''simple docstring'''

           kwargs.update(self.special_tokens_map )
           return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname				,    **UpperCamelCase_ )







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )

           # check adding a single token
           tokenizer.add_tokens('xxx' )
           __magic_name__      				=    tokenizer('m xxx ɪ'				,    do_phonemize=UpperCamelCase_ ).input_ids
           self.assertEqual(UpperCamelCase_				,    [1_3, 3_9_2, 1_7] )  # xxx should be last token

           tokenizer.add_tokens(['aaa', 'bbb', 'ccc'] )
           __magic_name__      				=    tokenizer('m aaa ɪ ccc'				,    do_phonemize=UpperCamelCase_ ).input_ids
           self.assertEqual(UpperCamelCase_				,    [1_3, 3_9_3, 1_7, 3_9_5] )  # aaa and ccc should be after xxx and 2 after aaa

           __magic_name__      				=    tokenizer('maɪ c'				,    do_phonemize=UpperCamelCase_ ).input_ids
           self.assertEqual(UpperCamelCase_				,    [3, 2_0_0] )  # mai should be <unk> (=3)







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )

           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )
           self.assertEqual(UpperCamelCase_				,    'h ə l oʊ h aʊ ɑːɹ j uː' )







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )

           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )
           self.assertEqual(tokenizer(UpperCamelCase_ ).input_ids				,    tokenizer(UpperCamelCase_				,    do_phonemize=UpperCamelCase_ ).input_ids )







    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )
           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )

           __magic_name__      				=    tokenizer.decode(tokenizer(UpperCamelCase_ ).input_ids )

           self.assertEqual(UpperCamelCase_				,    UpperCamelCase_ )







    def 				a__			(		self :	str ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )

           __magic_name__      				=    [
               [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 8, 9_8],
               [2_4, 2_2, 5, 2_4, 2_2, 5, 7_7],
           ]
           __magic_name__      				=    tokenizer.decode(sample_ids[0] )
           __magic_name__      				=    tokenizer.batch_decode(UpperCamelCase_ )
           self.assertEqual(UpperCamelCase_				,    batch_tokens[0] )
           self.assertEqual(UpperCamelCase_				,    ['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ'] )







    def 				a__			(		self :	List[str] ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained(
               'facebook/wav2vec2-lv-60-espeak-cv-ft'				,    word_delimiter_token='|' )
           tokenizer.add_tokens('|' )

           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )
           self.assertEqual(UpperCamelCase_				,    'h ə l oʊ | h aʊ | ɑːɹ | j uː |' )







    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained(
               'facebook/wav2vec2-lv-60-espeak-cv-ft'				,    word_delimiter_token='|' )
           tokenizer.add_tokens('|' )

           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )
           self.assertEqual(tokenizer(UpperCamelCase_ ).input_ids				,    tokenizer(UpperCamelCase_				,    do_phonemize=UpperCamelCase_ ).input_ids )







    def 				a__			(		self :	Union[str, Any] ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained(
               'facebook/wav2vec2-lv-60-espeak-cv-ft'				,    word_delimiter_token='|' )
           tokenizer.add_tokens('|' )

           # fmt: off
           __magic_name__      				=    [
               [1_1, 5, 1_5, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 1_5, 8, tokenizer.word_delimiter_token_id, 9_8],
               [tokenizer.word_delimiter_token_id, 2_4, 2_2, tokenizer.word_delimiter_token_id, 5, 2_4, 2_2, 5, 7_7],
           ]
           # fmt: on

           # decode with word_del_token filter
           __magic_name__      				=    tokenizer.decode(sample_ids[0] )
           __magic_name__      				=    tokenizer.batch_decode(UpperCamelCase_ )
           self.assertEqual(UpperCamelCase_				,    batch_tokens[0] )
           self.assertEqual(UpperCamelCase_				,    ['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ'] )

           # decode with no word_del_token filter
           __magic_name__      				=    tokenizer.decode(sample_ids[0]				,    filter_word_delimiter_token=UpperCamelCase_ )
           __magic_name__      				=    tokenizer.batch_decode(UpperCamelCase_				,    filter_word_delimiter_token=UpperCamelCase_ )
           self.assertEqual(UpperCamelCase_				,    batch_tokens[0] )
           self.assertEqual(UpperCamelCase_				,    ['k s ɾ | ɾ l | ɭʲ', '| j ð | s j ð s oːɹ'] )







    def 				a__			(		self :	List[str] ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained(
               'facebook/wav2vec2-lv-60-espeak-cv-ft'				,    word_delimiter_token='|' )
           tokenizer.add_tokens('|' )

           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )

           __magic_name__      				=    tokenizer.decode(tokenizer(UpperCamelCase_ ).input_ids				,    filter_word_delimiter_token=UpperCamelCase_ )

           self.assertEqual(UpperCamelCase_				,    UpperCamelCase_ )







    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained(
               'facebook/wav2vec2-lv-60-espeak-cv-ft'				,    word_delimiter_token='|' )
           tokenizer.add_tokens('|' )

           __magic_name__      				=    'Hello how are you'
           __magic_name__      				=    tokenizer.phonemize(UpperCamelCase_				,    phonemizer_lang='en-us' )

           __magic_name__      				=    tokenizer.decode(tokenizer(UpperCamelCase_ ).input_ids				,    filter_word_delimiter_token=UpperCamelCase_ )

           self.assertEqual(' '.join([p.strip() for p in phonemes.split(' |' )] ).strip()				,    UpperCamelCase_ )







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained(
               'facebook/wav2vec2-lv-60-espeak-cv-ft'				,    word_delimiter_token=UpperCamelCase_ )
           __magic_name__      				=    'Hello how are you'

           __magic_name__      				=    tokenizer(UpperCamelCase_				,    phonemizer_lang='en-us' ).input_ids
           __magic_name__      				=    tokenizer(UpperCamelCase_				,    phonemizer_lang='fr-fr' ).input_ids

           self.assertNotEqual(UpperCamelCase_				,    UpperCamelCase_ )

           __magic_name__      				=    tokenizer.decode(UpperCamelCase_ )
           __magic_name__      				=    tokenizer.decode(UpperCamelCase_ )

           self.assertEqual(UpperCamelCase_				,    'h ə l oʊ h aʊ ɑːɹ j uː' )
           self.assertEqual(UpperCamelCase_				,    'ɛ l o h aʊ a ʁ j u' )







    def 				a__			(		self :	Any ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )
           __magic_name__      				=    'Hello how Are you'
           __magic_name__      				=    'hello how are you'

           __magic_name__      				=    tokenizer(UpperCamelCase_ ).input_ids
           __magic_name__      				=    tokenizer(UpperCamelCase_ ).input_ids

           self.assertEqual(UpperCamelCase_				,    UpperCamelCase_ )







    def 				a__			(		self :	Any ):





           '''simple docstring'''

           __magic_name__      				=    self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )
           tokenizer.add_tokens(['!', '?'] )
           tokenizer.add_special_tokens({'cls_token': '$$$'} )

           # fmt: off
           __magic_name__      				=    [
               [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 8, 9_8, 3_9_2, 3_9_2, 3_9_3, 3_9_2, 3_9_2, 3_9_3, 3_9_4, 3_9_4],
               [2_4, 2_2, 5, 2_4, 2_2, 5, 7_7, tokenizer.pad_token_id, 3_9_4, 3_9_4],
           ]
           # fmt: on

           __magic_name__      				=    tokenizer.batch_decode(UpperCamelCase_ )
           self.assertEqual(UpperCamelCase_				,    ['k s ɾ ɾ l ɭʲ!?!? $$$', 'j ð s j ð s oːɹ $$$'] )







    @staticmethod
    def 				a__			(		UpperCamelCase_ :	Any				,    UpperCamelCase_ :	Tuple ):





           '''simple docstring'''

           __magic_name__      				=    [d[key] for d in offsets]
           return retrieved_list







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    self.get_tokenizer(word_delimiter_token='|' )
           tokenizer.add_tokens('|' )

           # fmt: off
           # ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
           __magic_name__      				=    [1_1, 5, 5, 5, 1_5, 1_5, tokenizer.pad_token_id, 1_5, 1_5, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 1_5, 8, 8, 8, tokenizer.word_delimiter_token_id, 9_8]
           # fmt: on

           __magic_name__      				=    tokenizer.decode(UpperCamelCase_				,    output_char_offsets=UpperCamelCase_				,    filter_word_delimiter_token=UpperCamelCase_ )
           # check Wav2Vec2CTCTokenizerOutput keys for char
           self.assertEqual(len(outputs.keys() )				,    2 )
           self.assertTrue('text' in outputs )
           self.assertTrue('char_offsets' in outputs )
           self.assertTrue(isinstance(UpperCamelCase_				,    UpperCamelCase_ ) )

           # check that order of chars is correct and identical for both outputs
           self.assertEqual(' '.join(self.get_from_offsets(outputs['char_offsets']				,    'char' ) )				,    outputs.text )
           self.assertListEqual(
               self.get_from_offsets(outputs['char_offsets']				,    'char' )				,    ['k', 's', 'ɾ', 'ɾ', '|', 'ɾ', 'l', '|', 'ɭʲ'] )

           # check that offsets are actually correct for char
           # 0-1 is 11, 1-4 is 5, 4-6 is first 15, 6-7 is <pad> (thus not shown), 7-9 is second 15, 9-10 is word_delimiter_token,
           # 10-11 is <pad> (thus not shown), 11-12 is third 15, 12-15 is 8, 15-16 is word_delimiter_token, 16-17 is 98
           self.assertListEqual(
               self.get_from_offsets(outputs['char_offsets']				,    'start_offset' )				,    [0, 1, 4, 7, 9, 1_1, 1_2, 1_5, 1_6] )
           self.assertListEqual(
               self.get_from_offsets(outputs['char_offsets']				,    'end_offset' )				,    [1, 4, 6, 9, 1_0, 1_2, 1_5, 1_6, 1_7] )







    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           __magic_name__      				=    self.get_tokenizer(word_delimiter_token='|' )

           def check_list_tuples_equal(UpperCamelCase_ :	Optional[Any]				,    UpperCamelCase_ :	List[str] ):
                  self.assertTrue(isinstance(UpperCamelCase_				,    UpperCamelCase_ ) )
                  self.assertTrue(isinstance(outputs_list[0]				,    UpperCamelCase_ ) )

                  # transform list to ModelOutput
                  __magic_name__      				=    WavaVecaPhonemeCTCTokenizerOutput(
                      {k: [d[k] for d in outputs_list] for k in outputs_list[0]} )

                  self.assertListEqual(outputs_batch['text']				,    outputs_batch_a['text'] )

                  def recursive_check(UpperCamelCase_ :	Any				,    UpperCamelCase_ :	Dict ):
                         if isinstance(UpperCamelCase_				,    UpperCamelCase_ ):
                                [recursive_check(UpperCamelCase_				,    UpperCamelCase_ ) for la, la in zip(UpperCamelCase_				,    UpperCamelCase_ )]
                         self.assertEqual(UpperCamelCase_				,    UpperCamelCase_ )

                  if "char_offsets" in outputs_batch:
                         recursive_check(outputs_batch['char_offsets']				,    outputs_batch_a['char_offsets'] )

        # fmt: off
           __magic_name__      				=    [
               [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 4, 8, 9_8, 3_2, 3_2, 3_2, 3_2, 4, 3_3, tokenizer.word_delimiter_token_id, 3_2, 3_2, 3_3, 3_4, 3_4],
               [2_4, 2_2, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 2_4, 2_2, 2_2, 2_2, 4, 5, 7_7, tokenizer.pad_token_id, 2_2, 2_2, 4, 3_4, 3_4, 3_4, 3_4],
           ]
           # fmt: on

           # We assume that `decode` works as expected. All we will check now is
           # the output type is correct and the output is identical to `decode`

           # char
           __magic_name__      				=    tokenizer.batch_decode(UpperCamelCase_				,    output_char_offsets=UpperCamelCase_ )
           __magic_name__      				=    [tokenizer.decode(UpperCamelCase_				,    output_char_offsets=UpperCamelCase_ ) for ids in sample_ids]
           check_list_tuples_equal(UpperCamelCase_				,    UpperCamelCase_ )







    @unittest.skip('Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes' )
    def 				a__			(		self :	Union[str, Any] ):





           '''simple docstring'''

           pass







    @unittest.skip('Wav2Vec2PhonemeTokenizer always puts spaces between phonemes' )
    def 				a__			(		self :	str ):





           '''simple docstring'''

           pass







    @unittest.skip('encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency' )
    def 				a__			(		self :	Any ):





           '''simple docstring'''

           pass







    @unittest.skip('Wav2Vec2PhonemeModel has no max model length => no testing' )
    def 				a__			(		self :	Optional[Any] ):





           '''simple docstring'''

           pass







    def 				a__			(		self :	str ):





           '''simple docstring'''

           __magic_name__      				=    self.get_tokenizers(do_lower_case=UpperCamelCase_ )
           for tokenizer in tokenizers:
                  with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
                         __magic_name__      				=    tokenizer.vocab_size
                         __magic_name__      				=    len(UpperCamelCase_ )

                         self.assertNotEqual(UpperCamelCase_				,    0 )

                         # We usually have added tokens from the start in tests because our vocab fixtures are
                         # smaller than the original vocabs - let's not assert this
                         # self.assertEqual(vocab_size, all_size)

                         __magic_name__      				=    ['aaaaa bbbbbb', 'cccccccccdddddddd']
                         __magic_name__      				=    tokenizer.add_tokens(UpperCamelCase_ )
                         __magic_name__      				=    tokenizer.vocab_size
                         __magic_name__      				=    len(UpperCamelCase_ )

                         self.assertNotEqual(UpperCamelCase_				,    0 )
                         self.assertEqual(UpperCamelCase_				,    UpperCamelCase_ )
                         self.assertEqual(UpperCamelCase_				,    len(UpperCamelCase_ ) )
                         self.assertEqual(UpperCamelCase_				,    all_size + len(UpperCamelCase_ ) )

                         __magic_name__      				=    tokenizer.encode('aaaaa bbbbbb low cccccccccdddddddd l'				,    add_special_tokens=UpperCamelCase_ )

                         self.assertGreaterEqual(len(UpperCamelCase_ )				,    4 )
                         self.assertGreater(tokens[0]				,    tokenizer.vocab_size - 1 )
                         self.assertGreater(tokens[-3]				,    tokenizer.vocab_size - 1 )

                         __magic_name__      				=    {'eos_token': '>>>>|||<||<<|<<', 'pad_token': '<<<<<|||>|>>>>|>'}
                         __magic_name__      				=    tokenizer.add_special_tokens(UpperCamelCase_ )
                         __magic_name__      				=    tokenizer.vocab_size
                         __magic_name__      				=    len(UpperCamelCase_ )

                         self.assertNotEqual(UpperCamelCase_				,    0 )
                         self.assertEqual(UpperCamelCase_				,    UpperCamelCase_ )
                         self.assertEqual(UpperCamelCase_				,    len(UpperCamelCase_ ) )
                         self.assertEqual(UpperCamelCase_				,    all_size_a + len(UpperCamelCase_ ) )

                         __magic_name__      				=    tokenizer.encode(
                             '>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'				,    add_special_tokens=UpperCamelCase_ )

                         self.assertGreaterEqual(len(UpperCamelCase_ )				,    6 )
                         self.assertGreater(tokens[0]				,    tokenizer.vocab_size - 1 )
                         self.assertGreater(tokens[0]				,    tokens[1] )
                         self.assertGreater(tokens[-3]				,    tokenizer.vocab_size - 1 )
                         self.assertGreater(tokens[-3]				,    tokens[-4] )
                         self.assertEqual(tokens[0]				,    tokenizer.eos_token_id )
                         self.assertEqual(tokens[-3]				,    tokenizer.pad_token_id )







    @unittest.skip('The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode.' )
    def 				a__			(		self :	Dict ):





           '''simple docstring'''

           pass







    @unittest.skip('The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode.' )
    def 				a__			(		self :	int ):





           '''simple docstring'''

           pass







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    self.get_tokenizers(fast=UpperCamelCase_				,    do_lower_case=UpperCamelCase_ )
           for tokenizer in tokenizers:
                  with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
                         __magic_name__      				=    ['ð', 'ɪ', 's', 'ɪ', 'z', 'ɐ', 't', 'ɛ', 'k', 's', 't']
                         __magic_name__      				=    tokenizer.convert_tokens_to_string(UpperCamelCase_ )

                         self.assertIsInstance(output['text']				,    UpperCamelCase_ )







"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


snake_case : int     		=		{}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case : str     		=		["""NllbTokenizer"""]

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case : Dict     		=		["""NllbTokenizerFast"""]


if TYPE_CHECKING:
 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_nllb import NllbTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_nllb_fast import NllbTokenizerFast

else:
 import sys

 snake_case : Dict     		=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)